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Advisors and Asset Prices: A Model of the Origins of Bubbles

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  • Harrison Hong
  • Jose Scheinkman
  • Wei Xiong

Abstract

We develop a model of asset price bubbles based on the communication process between advisors and investors. Advisors are well-intentioned and want to maximize the welfare of their advisees (like a parent treats a child). But only some advisors understand the new technology (the tech-savvies); others do not and can only make a downward-biased recommendation (the old-fogies). While smart investors recognize the heterogeneity in advisors, naive ones mistakenly take whatever is said at face value. Tech-savvies inflate their forecasts to signal that they are not old-fogies, since more accurate information about their type improves the welfare of investors in the future. A bubble arises for a wide range of parameters, and its size is maximized when there is a mix of smart and naive investors in the economy. Our model suggests an alternative source for stock over-valuation in addition to investor overreaction to news and sell-side bias.
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Suggested Citation

  • Harrison Hong & Jose Scheinkman & Wei Xiong, 2005. "Advisors and Asset Prices: A Model of the Origins of Bubbles," Levine's Bibliography 122247000000001003, UCLA Department of Economics.
  • Handle: RePEc:cla:levrem:122247000000001003
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    File URL: http://www.princeton.edu/~wxiong/papers/advisor.pdf
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    References listed on IDEAS

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    Cited by:

    1. Kaustia, Markku & Lehtoranta, Antti & Puttonen, Vesa, 2013. "Does sophistication affect long-term return expectations? Evidence from financial advisers' exam scores," SAFE Working Paper Series 3, Research Center SAFE - Sustainable Architecture for Finance in Europe, Goethe University Frankfurt.
    2. repec:nax:conyad:v:62:y:2017:i:4:p:1317-1334 is not listed on IDEAS
    3. Beltratti, Andrea & Bortolotti, Bernardo & Caccavaio, Marianna, 2016. "Stock market efficiency in China: Evidence from the split-share reform," The Quarterly Review of Economics and Finance, Elsevier, vol. 60(C), pages 125-137.
    4. Alice Hsiaw & Ing-Haw Cheng, 2016. "Distrust in Experts and the Origins of Disagreement," Working Papers 110, Brandeis University, Department of Economics and International Businesss School.
    5. Chollete, Loran, 2011. "A Model of Endogenous Extreme Events," UiS Working Papers in Economics and Finance 2012/2, University of Stavanger.
    6. Stijn Claessens & M. Ayhan Kose, 2013. "Financial Crises: Explanations, Types and Implications," CAMA Working Papers 2013-06, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Greenwood, Robin & Nagel, Stefan, 2009. "Inexperienced investors and bubbles," Journal of Financial Economics, Elsevier, vol. 93(2), pages 239-258, August.
    8. Glaeser, Edward L. & Gyourko, Joseph & Saiz, Albert, 2008. "Housing supply and housing bubbles," Journal of Urban Economics, Elsevier, vol. 64(2), pages 198-217, September.
    9. Edward L. Glaeser & Charles G. Nathanson, 2014. "Housing Bubbles," NBER Working Papers 20426, National Bureau of Economic Research, Inc.
    10. Lubos Pastor & Pietro Veronesi, 2009. "Learning in Financial Markets," Annual Review of Financial Economics, Annual Reviews, vol. 1(1), pages 361-381, November.
    11. William A. Branch & George W. Evans, 2011. "Learning about Risk and Return: A Simple Model of Bubbles and Crashes," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(3), pages 159-191, July.
    12. James Hansen, 2011. "Does Equity Mispricing Influence Household and Firm Decisions?," RBA Research Discussion Papers rdp2011-06, Reserve Bank of Australia.
    13. Anna Scherbina, 2013. "Asset Price Bubbles; A Selective Survey," IMF Working Papers 13/45, International Monetary Fund.
    14. Yang, G. & Chen, Y. & Huang, J.P., 2016. "The highly intelligent virtual agents for modeling financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 98-108.
    15. Chollete, Loran & Jaffee, Dwight, 2009. "Economic Implications of Extreme and Rare Events," UiS Working Papers in Economics and Finance 2009/32, University of Stavanger.
    16. Alda, Mercedes, 2017. "The relationship between pension funds and the stock market: Does the aging population of Europe affect it?," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 83-97.
    17. Zeng, Yeqin, 2016. "Institutional investors: Arbitrageurs or rational trend chasers," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 240-262.
    18. Bianchi, Milo & Jehiel, Philippe, 2015. "Financial reporting and market efficiency with extrapolative investors," Journal of Economic Theory, Elsevier, vol. 157(C), pages 842-878.
    19. Hackethal, Andreas & Inderst, Roman & Meyer, Steffen, 2010. "Trading on Advice," CEPR Discussion Papers 8091, C.E.P.R. Discussion Papers.
    20. Linnenluecke, Martina K. & Smith, Tom & McKnight, Brent, 2016. "Environmental finance: A research agenda for interdisciplinary finance research," Economic Modelling, Elsevier, vol. 59(C), pages 124-130.
    21. Ning, Cathy, 2010. "Dependence structure between the equity market and the foreign exchange market-A copula approach," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 743-759, September.
    22. Stefano Giglio & Matteo Maggiori & Johannes Stroebel, 2016. "No‐Bubble Condition: Model‐Free Tests in Housing Markets," Econometrica, Econometric Society, vol. 84, pages 1047-1091, May.
    23. Chollete, Loran & Ning, Cathy, 2010. "Asymmetric Dependence in US Financial Risk Factors?," UiS Working Papers in Economics and Finance 2011/2, University of Stavanger.
    24. Glaeser, Edward L. & Nathanson, Charles G., 2015. "Housing Bubbles," Handbook of Regional and Urban Economics, Elsevier.
    25. Joseph Gyourko, 2009. "Understanding Commercial Real Estate: Just How Different from Housing Is It?," NBER Working Papers 14708, National Bureau of Economic Research, Inc.

    More about this item

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G2 - Financial Economics - - Financial Institutions and Services

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